A NMF-based collaborative filtering recommendation algorithm

被引：0

作者：

Li, Tao ^{[1
,2
]}

Wang, Jiandong ^{[1
]}

Chen, Huiping ^{[1
]}

Feng, Xinyu ^{[1
]}

Ye, Feiyue ^{[1
]}

机构：

[1] Nanjing Univ Aeronaut & Astronaut, Coll Informat Sci & Technol, Nanjing 210016, Peoples R China

[2] Nanjing Univ Informat Sci & Technol, Dept Informat & Commun, Nanjing 210044, Jiangsu, Peoples R China

来源：

WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS | 2006年

关键词：

recommender system; collaborative filtering; non-negative matrix factorization;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Recommender systems are becoming increasingly popular with the evolution of the Internet, and collaborative filtering (CF) is one of the most important technologies in recommender systems. Such technology recommends items to a customer according to the preference data of similar customers. The performance of CF systems degrades with increasing number of customers and items. To reduce the dimensionality of filtering databases and to improve the performance, non-negative matrix factorization (NMF) is applied to CF. The experiment results show that NMF-based CF can improve the performance of CF systems in both the recommendation quality and efficiency.

引用

页码：6082 / +

页数：3

共 19 条

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